Gait-based person and gender recognition using micro-doppler signatures (original) (raw)

2011 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2011

Abstract

Abstract The ability to identify an individual quickly and accurately is a critical parameter in surveillance. Conventional contactless systems are often complex and expensive to implement since video-based processing requires high computational resources. In this paper we present a micro-Doppler (mD) system and a computationally efficient classifier for the purpose of identifying individuals and gender. Walking subjects are successfully classified based on their mD time-frequency signatures. Recognition accuracies as high ...

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